omni.ate: Omnibus function for estimation and testing

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/omni.ate.R

Description

Estimates the average treatment effect (ATE) and inferential statistics under constant effects hypotheses. Estimation is without covariate adjustment, via weighted least squares.

Usage

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omni.ate(Y, Z, perms, invert = FALSE, quantiles = c(0.025, 0.975))

Arguments

Y

numeric vector of length N, outcome variable

Z

binary vector (0 or 1) of length N, treatment indicator

perms

N-by-r permutation matrix, as output by genperms or genperms.custom

invert

logical for generating constant effects confidence intervals through exact test inversion, with the difference-in-means as a test statistic. Default is FALSE.

quantiles

vector of quantiles of the randomization distribution to be returned. Quantiles also used to determine endpoints of confidence intervals. Default is equal-tailed 95% intervals.

Details

omni.ate() is a convenience function that implements a number of functions otherwise available in ri. Greater flexibility through use of the individual functions involved.

Value

ate

estimated average treatment effect

greater.p.value

one-tailed p-value: proportion of randomizations yielding estimated ATE greater than or equal to hypothesized ATE

lesser.p.value

one-tailed p-value: proportion of randomizations yielding estimated ATE less than or equal to hypothesized ATE

p.value

two-tailed p-value: twice the smaller of the two one-tailed p-values, as advocated by Rosenbaum (2002)

p.value.alt

two-tailed p-value: proportion of randomizations yielding absolute estimated ATE greater than or equal to absolute hypothesized ATE

se.null

standard error of the randomization distribution assuming a zero treatment effect

conf.int

confidence interval approximation under a constant effect hypothesis

se

standard error of the randomization distribution assuming a constant treatment effect equal to the estimated ATE

conf.intInv

(Optional, if invert=TRUE) confidence interval under an inverted exact test with the difference-in-means as a test statistic

Author(s)

Peter M. Aronow <[email protected]>; Cyrus Samii <[email protected]>

References

Gerber, Alan S. and Donald P. Green. 2012. Field Experiments: Design, Analysis, and Interpretation. New York: W.W. Norton.

Rosenbaum, Paul R. 2002. Observational Studies. 2nd ed. New York: Springer.

Samii, Cyrus and Peter M. Aronow. 2012. On Equivalencies Between Design-Based and Regression-Based Variance Estimators for Randomized Experiments. Statistics and Probability Letters. 82(2): 365-370. http://dx.doi.org/10.1016/j.spl.2011.10.024

See Also

ri

Examples

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y <- c(8,6,2,0,3,1,1,1,2,2,0,1,0,2,2) 
Z <- c(1,1,0,0,1,1,0,0,1,1,1,1,0,0,1)

perms <- genperms(Z) # all possible permutations of assignment

omni.ate(y,Z,perms,FALSE)
# omni.ate(y,Z,perms,TRUE) # may take some time to run

ri documentation built on May 2, 2019, 6:51 a.m.